2. Use of Data, AI and Advanced Analytics

Data is the fuel of the digital economy and the foundation for all the trends and predictions in 2017. Unfortunately, while the consumer has indicated a willingness to share information about themselves with banks and credit unions, the ability for financial institutions to leverage this insight has been far short of optimal.

The Digital Banking Report, Power of Personalization in Banking, found that many customers will share their data with bank brands if they get something valuable in return. The desired reward? Offers customized to their individual wants and needs.

Unfortunately, the clear majority of organizations are collecting customer data and not doing anything with it that benefits the customer. Beyond neglect, this practice could also be killing an organization’s future and ensuring greater share of wallet go to your competitors.

In the IBM report, “The Cognitive Bank: Decoding Data to Bolster Growth and Transform the Enterprise“, it is emphasized that tapping into huge quantities of dormant, bank-owned data is essential to offering the individualized engagement that customers demand. It is also proposed that cognitive systems can continually build knowledge and learning, providing the insight needed to increase efficiency and effectiveness throughout the organization. In other words, the one to one future on steroids.

Ultimately, cognitive computing enables banks to exploit the benefits of available data by:

Providing deeper and more personalized customer insight

Supporting more-informed decisions across the whole bank

Accelerating operational and organizational efficiency

By combining internal and external data (both structured and unstructured), banks and credit unions can position their organizations at the center of rapidly evolving banking ecosystems. Because legacy banking organizations have such a wealth of knowledge, cognitive banking organizations can provide ‘doorways’ for existing fintech firms to build relationships with households they could not reach or serve before.

The promises and hype around big data, advanced analytics and AI have yet to be realized for many financial institutions, states Ron Shevlin. “It’s not because of a lack of statistical and analytical tools and techniques. It’s not necessarily because of the lack of access to the data available. And it’s not necessarily because of data “cleanliness” issues. It has a lot to do with the fact that the data that is available isn’t predictive or descriptive. It’s the wrong data.”

While financial institutions make a big deal about having payment data available, Shevlin asks the simple question, “What does payment data do? It certainly helps retailers and merchants (and Apple) pitch offers. But, that’s not what customers want from their banks.”

The term gentrification typically refers to the renovation and improvement of rundown properties. Shevlin argues that banks’ data warehouses are similar … rundown properties in need of gentrification.

“Over the next few years, banks will embark on data gentrification efforts – not just cleaning up the data they have, but collecting and using BETTER data. Data that better predicts and explains consumers’ financial health, directions and trends in their financial health, and actions needed to better improve financial lives.”

“The use of data really is now becoming a mandatory tool to assist the customer, employee and the CEO. Going forward, data will be embedded and detected on a real-time basis, driving decisions on efficiency, experience improvement, and margin gains. Banks and credit unions will look to large technology companies as the standard in data-responsive design and development, and will seek to automate not just measurement, but also improvement and process.”
– Rob Findlay, Founder of Next Money

“2017 is the year to marry Tech + Touch. Find a balance between accelerated digital adoption and the human touch. It’s time that banks start using data to digitally personalize customer interactions.”
– Vikram Krishna, EVP and Head of Group Marketing at Emirates NBD

“Retail banking should have been transformed by data analytics late last century but it was not. The rise of fintech and the 2008 financial crisis have ushered in a new focus on data (cognitive computing, AI, predictive analytics, etc.) throughout the entire organization, with operational excellence and digital transformation being key. 2017 will be the year when financial service providers who have embraced these tenants will begin to separate from those who have not.”

“Banks and credit unions will be challenged to deliver digital experiences that mimic the human assistance that consumers get in other channels – such as the branch and call center. Through artificial intelligence, banks and credit unions can breathe life into consumer interactions. With artificial intelligence as the face of the digital interaction, other technologies such as natural language processing, predictive analytics, biometrics, among many other technologies, become the guts that stitch together an experience that drive interactions through every stage of the consumer lifecycle.”
– Tiffani Montez, Senior Analyst at Aite Group

2017 will herald in the 5th age of banking – the analytics age. Financial Institutions will face an unprecedented opportunity to be true advocates for consumers by utilizing data to the same level as other disrupted industries (think Amazon or Netflix). Consumers enjoy unprecedented choice and virtually no friction to change. FI’s who do not embrace data will find themselves beautifully equipped for a world that no longer exists.”

“Machine Learning and Artificial Intelligence will begin to be applied beyond robo-advisors and activity to leverage these technologies will begin to take hold. 2017 is likely to be a transitional year where pilots inform longer term product development.”
– Dominic Venturo, EVP and Chief Innovation Officer at U.S. Bank

“2017 will be the year that predictive analytics will hit the big time in retail bank marketing. Banks will boost their top line with ‘next best product’, social media, and customer retention analyses.”
– Steven Ramirez, CEO of Beyond the Arc

“Machine learning and artificial intelligence are transforming other industries. Banking is just getting started building out greater efficiencies using these tools and leveraging the data we’ve neglected for decades. Banking apps will deliver personalized financial advice by leveraging aggregated financial data across a consumer’s providers in the future. Forget robo-advisors for investments only … our entire financial life will have a robo-component. And we will be better off for it.”

“Smart use of data can enable us to reestablish personalized services and bring back customized one-to-one relationships between the bank and the customer. The upcoming PSD2 (and US equivalent) will alter how the data is stored and used, with bots, machine learning, and adaptive technologies all playing a role. Nailing this (data) step is essential to progress towards the banking-as-a-platform model, which is the future of finance.
– Alex Nechoroskovas, Founder of Fintech Summary

“Predictive analytics move from theory and early beginnings to broader and more prevalent application. Recurring transactions become easier to undertake and product recommendations become more pro-active and relevant.”
– Nick Bilodeau, Head of Insurance (Canada) for American Express

“All of the business models we have seen created and funded in fintech over the past 8 years will be revisited with an AI component – be it machine learning, deep learning or other. This is bound to happen as AI is sweeping the business world. If mobile is eating the world, AI is the chef that is orchestrating the menu.”

Jim Marous is co-publisher of The Financial Brand and publisher of the Digital Banking Report, a subscription-based publication that provides deep insights into the digitization of banking, with over 150 reports in the digital archive available to subscribers. You can follow Jim on Twitter and LinkedIn, or visit his professional website.

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